Machine Learning & Data Science · head to head
Neptune.ai vs Apache Spark MLlib

Apache Spark MLlib
Machine Learning & Data Science
Scalable machine learning on Apache Spark
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Neptune.ai free tier limited to 100 hours per month, exhausted quickly with serious ML work; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
- They diverge on capability: Neptune.ai covers Experiment tracking, Apache Spark MLlib covers Classification.
Where they differ
Only the attributes on which Neptune.ai and Apache Spark MLlib actually diverge.
| Attribute | Neptune.ai | Apache Spark MLlib |
|---|---|---|
| Pricing model | Unknown | open-source |
| Platforms | Web, Self-hosted | Linux, macOS, Windows |
| Founded | 2017 | 1999 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Neptune.ai
- Experiment tracking
- Model registry
- Metadata logging
- Comparison views
- Custom dashboards
- PyTorch
- TensorFlow
- Keras
Only in Apache Spark MLlib
- Classification
- Regression
- Clustering
- Collaborative filtering
- Feature engineering
- Apache Spark
- Hadoop
- Kafka
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
Neptune.ai
- Machine learningnot Apache Spark MLlib
- Data analysisnot Apache Spark MLlib
- Model trainingnot Apache Spark MLlib
- Predictive analyticsnot Apache Spark MLlib
Apache Spark MLlib
- Large-scale distributed machine learning on Spark clustersnot Neptune.ai
- Classification and regression with decision trees, random forests, gradient-boosted treesnot Neptune.ai
- Clustering with K-means and Gaussian Mixture Modelsnot Neptune.ai
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Neptune.ai
- Free tier limited to 100 hours per month, exhausted quickly with serious ML work
- Lacks hyperparameter sweeps compared to Weights and Biases
- No pipeline orchestration or broader MLOps lifecycle management
- Dashboard visualization limitations - automatic resizing affects visualization order and size
- Cloud-based SaaS only (as of last available service) requires internet connectivity
Apache Spark MLlib
- Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
Pricing, plan by plan
Neptune.ai
FreeNo published plan breakdown. See the Neptune.ai review.
Apache Spark MLlib
FreeNo published plan breakdown. See the Apache Spark MLlib review.
Which should you pick?
Choose Neptune.ai if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Self-hosted.
- You also want model registry.
Choose Apache Spark MLlib if
- You need classification.
- You want to start without paying.
- You work on Linux, macOS, Windows.
- You also want regression.
Questions people ask
- Is Neptune.ai or Apache Spark MLlib better?
- Neither clearly leads. Neptune.ai starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Neptune.ai or Apache Spark MLlib?
- Neptune.ai starts at Free and Apache Spark MLlib at Free.
- Does Neptune.ai or Apache Spark MLlib run on more platforms?
- Neptune.ai runs on Web, Self-hosted. Apache Spark MLlib runs on Linux, macOS, Windows.
- Can I use Neptune.ai for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Neptune.ai best used for?
- Neptune.ai is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Apache Spark MLlib is typically brought in for.
- What can Neptune.ai do that Apache Spark MLlib cannot?
- Neptune.ai covers Experiment tracking, Model registry, Metadata logging, Comparison views. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Linux support, Mac support, Windows support.
Answered from the vendors’ own pages
Neptune.ai: Does Neptune.ai support self-hosting?
Yes. Neptune can be self-hosted on a Kubernetes cluster with ClickHouse, MySQL, and Redis dependencies, allowing organizations to maintain full data control.
SourceNeptune.ai: What machine learning frameworks does Neptune integrate with?
Neptune integrates with PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Hugging Face Transformers, and Optuna for hyperparameter optimization.
SourceNeptune.ai: What is the cost for a team of 10 data scientists?
Neptune's Team plan costs $49 per user per month, resulting in $490/month for 10 users, comparable to Weights and Biases at $50/user.
SourceNeptune.ai: When is Neptune.ai shutting down?
Neptune.ai is shutting down its external SaaS service on March 5, 2026, following its acquisition by OpenAI in December 2025. Customers must export and migrate data before that date.
SourceRelated pages
More on Apache Spark MLlib
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- Apache Spark MLlib vs Azure Machine Learning
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- Apache Spark MLlib vs Comet ML
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